No abstract

This paper investigates the machining stability in ball-end-milling of curved surface in which the inclination of tool continuously changes. Initially, the influence of inclination angle is geometrically investigated on the parameters such as immersion angle and cutting velocity. Then, the paper presents the stability lobe diagrams of the process. Curved surface milling is simulated by slot milling on a cylindrical workpiece using a ball-end-mill to obtain the cutting force and vibration, which are used for fast-Fourier transform and Hilbert-Huang transform (HHT) analyses. Experimental results show that the cutting force increases, and the stability becomes worse with the inclination angle, while the machining errors decrease with the inclination. The vibration analysis showed that the HHT can detect the transition from stable to unstable during milling of curved surface in the time-frequency plots.

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In face milling process of train wheel, cutter is one of the most important part and this part should be monitored from failure phenomena for improving final products of train wheel during machining process. One of the best ways for face milling tool condition monitoring is by analyzing signal. However, noise usually contaminates the measured signals during measurement using any sensors. This study presents the effect of noise on the Hilbert-Huang transform features for face milling condition monitoring by mean analyzing the synthetic vibration signals. First, noisy synthetic signals were created, then separates them by Empirical Mode Decomposition (EMD) to be intrinsic mode decompositions (IMFs). Second, the Hilbert-Huang spectra were generated and then compared to HHT baseline spectrum. The result showed that the noise disturbed the HHT spectrum. Without filtering signal, the face milling cutter condition phenomenon was difficult to be revealed by HHT.

Abstract-The chassis design has been done for rural transportation vehicles in